About the Team

Bloomberg’s CTO Office is the future-looking technical and product arm of Bloomberg L.P. We envision, design, and prototype the next generation of infrastructure, hardware, and applications that power the Bloomberg Terminal and beyond. Our work spans AI platforms, cloud infrastructure, open-source stewardship, and generative AI innovation.

For over a decade, Bloomberg has been at the forefront of applying artificial intelligence, ML, and NLP to financial intelligence, powering products in sentiment analysis, classification, document understanding, recommendation, and generative AI. Critical to this effort are our AI platforms, which enable teams to rapidly and robustly build, deploy, evaluate, govern, and operate AI systems at scale.

As Bloomberg expands its investment in Generative and Agentic AI, we are scaling the model, cloud, compute, data, and infrastructure foundations that power the next generation of intelligent products across Terminal, Enterprise, and client-facing experiences.

What’s In It For You

We are looking for a Technical Product Manager to define and execute foundational capabilities for AI Infrastructure: the cloud, compute, data, networking, and runtime foundations behind Bloomberg’s AI platforms and AI-powered products.

You will help shape how teams experiment with, access, deploy, serve, and operate AI models across a range of infrastructure environments, while turning rapidly evolving model, cloud, and compute capabilities into reliable and reusable platform services. You will help define common platform abstractions and paved paths that give product teams consistent ways to access AI infrastructure, while allowing the underlying models, hardware, and cloud environments to evolve.

This role sits at the intersection of AI Platforms, agentic systems, cloud infrastructure, and distributed systems. You will work across engineering and product teams to improve the scalability, reliability, performance, and efficiency of Bloomberg’s AI infrastructure while preserving flexibility as models, providers, hardware, and workload patterns evolve.

This is a cross-cutting role by design. You’ll need to be comfortable working across product and organizational boundaries, identifying common infrastructure needs, establishing platform direction, and driving alignment in an area where both the technology and the architecture are evolving quickly.

Why This Matters

The infrastructure behind modern AI systems is becoming increasingly heterogeneous. Product teams may need to choose between frontier and specialized models, managed APIs and internally hosted models, public and private cloud infrastructure, different accelerator technologies, and different serving or training patterns. Increasingly, teams must also decide where workloads execute and where data resides. Data locality, network topology, accelerator availability, regulatory constraints, and cloud placement can have significant implications for quality, latency, throughput, capacity, availability, security, and cost. Bloomberg needs common infrastructure foundations that allow product teams to take advantage of advances in AI without independently solving model hosting, provider integration, capacity management, reliability, and cloud infrastructure challenges.

We’ll trust you to

• Define and drive the vision for Bloomberg’s AI Infrastructure, with a focus on infrastructure across models, compute, and cloud

• Work directly with AI product and engineering teams to understand their requirements for model quality, performance, scale, reliability, and cost, and translate common needs into reusable platform capabilities

• Partner deeply with engineering to deliver scalable, resilient system architecture

• Partner with cloud and infrastructure teams to advance hybrid and multi-cloud capabilities, including portability, resilience, scalability, and integration with model and cloud providers

• Evaluate advances across cloud platforms, model providers, infrastructure services, model-serving technologies, accelerators, and emerging AI infrastructure capabilities, and translate them into pragmatic platform opportunities and roadmap decisions

• Establish product metrics and strategies for improving latency, throughput, availability, utilization, capacity, and cost efficiency across AI workloads

• Partner deeply with Engineering and stakeholders across AI Platforms, Cloud, Security, and other infrastructure organizations to align priorities, dependencies, and investments

• Anticipate how AI workloads and infrastructure requirements will evolve, balancing standardization and paved paths with flexibility and choice

You’ll Need to Have

• 5+ years of experience in technical product management, ideally within AI, platform, cloud, compute, or infrastructure domains

• Experience building, operating, or product managing large-scale platform infrastructure used by internal or external developers

• Experience with public cloud platforms such as AWS, GCP, or Azure, and familiarity with hybrid or multi-cloud architecture

• Strong understanding of distributed systems, service-to-service communication, API Gateways, Kubernetes, cloud-native architectures, and service reliability

• Technical fluency in the tradeoffs involved in operating AI workloads, including latency, throughput, availability, scalability, accelerator utilization, and cost

• Familiarity working with AI or GenAI systems, with LLMs, generative AI, and their production requirements

• Proven ability to work cross-functionally with engineering, security, product, and platform organizations

• Excellent communication and storytelling skills, with the ability to translate between user needs, business priorities, and technical architecture, and influence across diverse teams

We’d Love to See

• A degree in Computer Science, Engineering, related technical disciplines, or prior equivalent practical experience

• Experience with GPU or accelerator infrastructure, HPC workloads, capacity planning, scheduling, or multi-tenant resource management

• Experience with AI infrastructure platforms, MLOps, inference or training platforms, model gateways, inference techniques, model-as-a-service offerings, model optimization

• Contributions to open-source infrastructure, AI, or developer ecosystems

• Familiarity with financial services or other large-scale, regulated enterprise environments

Why Join Us

You will play a pivotal role in shaping Bloomberg’s AI future by building the infrastructure foundations that enable trusted, scalable, and production-ready AI systems. This is an opportunity to help define how AI systems operate at enterprise scale. You will work alongside world-class engineers, architects, researchers, and product leaders while helping establish the trusted infrastructure foundation that powers Bloomberg’s next generation of AI innovation.